tbuckley/cabot-search huggingface dataset:
Revealing nanostructures in brain tissue via protein decrowding by iterative expansion microscopy
Authors: Deblina Sarkar, Jinyoung Kang, Asmamaw T. Wassie, Margaret E. Schroeder, Zhuyu Peng, Tyler B. Tarr, Ai-Hui Tang, Emily D. Niederst, Jennie Z. Young, Hanquan Su, Demian Park, Peng Yin, Li-Huei Tsai, Thomas A. Blanpied, Edward S. Boyden
Journal: Nature Biomedical Engineering (2022)
Large-scale sequencing identifies multiple genes and rare variants associated with Crohn’s disease susceptibility
Authors: Aleksejs Sazonovs, Christine R. Stevens, Guhan R. Venkataraman, Kai Yuan, Brandon Avila, Maria T. Abreu, Tariq Ahmad, Matthieu Allez, Ashwin N. Ananthakrishnan, Gil Atzmon, Aris Baras, Jeffrey C. Barrett, Nir Barzilai, Laurent Beaugerie, Ashley Beecham, Charles N. Bernstein, Alain Bitton, Bernd Bokemeyer, Andrew Chan, Daniel Chung, Isabelle Cleynen, Jacques Cosnes, David J. Cutler, Allan Daly, Oriana M. Damas, Lisa W. Datta, Noor Dawany, Marcella Devoto, Sheila Dodge, Eva Ellinghaus, Laura Fachal, Martti Farkkila, William Faubion, Manuel Ferreira, Denis Franchimont, Stacey B. Gabriel, Tian Ge, Michel Georges, Kyle Gettler, Mamta Giri, Benjamin Glaser, Siegfried Goerg, Philippe Goyette, Daniel Graham, Eija Hämäläinen, Talin Haritunians, Graham A. Heap, Mikko Hiltunen, Marc Hoeppner, Julie E. Horowitz, Peter Irving, Vivek Iyer, Chaim Jalas, Judith Kelsen, Hamed Khalili, Barbara S. Kirschner, Kimmo Kontula, Jukka T. Koskela, Subra Kugathasan, Juozas Kupcinskas, Christopher A. Lamb, Matthias Laudes, Chloé Lévesque, Adam P. Levine, James D. Lewis, Claire Liefferinckx, Britt-Sabina Loescher, Edouard Louis, John Mansfield, Sandra May, Jacob L. McCauley, Emebet Mengesha, Myriam Mni, Paul Moayyedi, Christopher J. Moran, Rodney D. Newberry, Sirimon O’Charoen, David T. Okou, Bas Oldenburg, Harry Ostrer, Aarno Palotie, Jean Paquette, Joel Pekow, Inga Peter, Marieke J. Pierik, Cyriel Y. Ponsioen, Nikolas Pontikos, Natalie Prescott, Ann E. Pulver, Souad Rahmouni, Daniel L. Rice, Päivi Saavalainen, Bruce Sands, R. Balfour Sartor, Elena R. Schiff, Stefan Schreiber, L. Philip Schumm, Anthony W. Segal, Philippe Seksik, Rasha Shawky, Shehzad Z. Sheikh, Mark S. Silverberg, Alison Simmons, Jurgita Skeiceviciene, Harry Sokol, Matthew Solomonson, Hari Somineni, Dylan Sun, Stephan Targan, Dan Turner, Holm H. Uhlig, Andrea E. van der Meulen, Séverine Vermeire, Sare Verstockt, Michiel D. Voskuil, Harland S. Winter, Justine Young, Richard H. Duerr, Andre Franke, Steven R. Brant, Judy Cho, Rinse K. Weersma, Miles Parkes, Ramnik J. Xavier, Manuel A. Rivas, John D. Rioux, Dermot P. B. McGovern, Hailiang Huang, Carl A. Anderson, Mark J. Daly
Journal: Nature Genetics (2022)
Pilot study of responsive nucleus accumbens deep brain stimulation for loss-of-control eating
Authors: Rajat S. Shivacharan, Camarin E. Rolle, Daniel A. N. Barbosa, Tricia N. Cunningham, Austin Feng, Noriah D. Johnson, Debra L. Safer, Cara Bohon, Corey Keller, Vivek P. Buch, Jonathon J. Parker, Dan E. Azagury, Peter A. Tass, Mahendra T. Bhati, Robert C. Malenka, James D. Lock, Casey H. Halpern
Journal: Nature Medicine (2022)

Abstract Cravings that precede loss of control (LOC) over food consumption present an opportunity for intervention in patients with the binge eating disorder (BED). In this pilot study, we used responsive deep brain stimulation (DBS) to record nucleus accumbens (NAc) electrophysiology during food cravings preceding LOC eating in two patients with BED and severe obesity (trial registration no. NCT03868670). Increased NAc low-frequency oscillations, prominent during food cravings, were used to guide DBS delivery. Over 6 months, we observed improved self-control of food intake and weight loss. These findings provide early support for restoring inhibitory control with electrophysiologically-guided NAc DBS. Further work with increased sample sizes is required to determine the scalability of this approach.
Extubation in neurocritical care patients: the ENIO international prospective study
Authors: Raphaël Cinotti, Julio Cesar Mijangos, Paolo Pelosi, Matthias Haenggi, Mohan Gurjar, Marcus J. Schultz, Callum Kaye, Daniel Agustin Godoy, Pablo Alvarez, Aikaterini Ioakeimidou, Yoshitoyo Ueno, Rafael Badenes, Abdurrahmaan Ali Suei Elbuzidi, Michaël Piagnerelli, Muhammed Elhadi, Syed Tariq Reza, Mohammed Atef Azab, Victoria McCredie, Robert D. Stevens, Jean Catherine Digitale, Nicholas Fong, Karim Asehnoune, Paër-sélim Abback, Anaïs Codorniu, Giuseppe Citerio, Vittoria Ludovica Sala, Marinella Astuto, Eleonora Tringali, Daniela Alampi, Monica Rocco, Jessica Giuseppina Maugeri, Agrippino Bellissima, Matteo Filippini, Nicoletta Lazzeri, Andrea Cortegiani, Mariachiara Ippolito, Chiara Robba, Denise Battaglini, Patrick Biston, Mohamed Fathi Al-Gharyani, Russell Chabanne, Léo Astier, Benjamin Soyer, Samuel Gaugain, Alice Zimmerli, Urs Pietsch, Miodrag Filipovic, Giovanna Brandi, Giulio Bicciato, Ainhoa Serrano, Berta Monleon, Peter van Vliet, Benjamin Marcel Gerretsen, Iris Xochitl Ortiz-Macias, Jun Oto, Noriya Enomoto, Tomomichi Matsuda, Nobutaka Masui, Pierre Garçon, Jonathan Zarka, Wytze J. Vermeijden, Alexander Daniel Cornet, Sergio Reyes Inurrigarro, Rafael Cirino Lara Domínguez, Maria Mercedes Bellini, Maria Milagros Gomez Haedo, Laura Lamot, Jose Orquera, Matthieu Biais, Delphine Georges, Arvind Baronia, Roberto Carlos Miranda-Ackerman, Francisco José Barbosa-Camacho, John Porter, Miguel Lopez-Morales, Thomas Geeraerts, Baptiste Compagnon, David Pérez-Torres, Estefanía Prol-Silva, Hana Basheer Yahya, Ala Khaled, Mohamed Ghula, Cracchiolo Neville Andrea, Palma Maria Daniela, Cristian Deana, Luigi Vetrugno, Manuel J. Rivera Chavez, Rocio Mendoza Trujillo, Vincent Legros, Benjamin Brochet, Olivier Huet, Marie Geslain, Mathieu van der Jagt, Job van Steenkiste, Hazem Ahmed, Alexander Edward Coombs, Jessie Welbourne, Ana Alicia Velarde Pineda, Víctor Hugo Nubert Castillo, Mohammed A. Azab, Ahmed Y. Azzam, David Michael Paul van Meenen, Gilberto Adrian Gasca, Alfredo Arellano, Forttino Galicia-Espinosa, José Carlos García-Ramos, Ghanshyam Yadav, Amarendra Kumar Jha, Vincent Robert-Edan, Pierre-Andre Rodie-Talbere, Gaurav Jain, Sagarika Panda, Sonika Agarwal, Yashbir Deewan, Gilberto Adrian Gasca, Alfredo Arellano, Syed Tariq Reza, Md. Mozaffer Hossain, Christos Papadas, Vasiliki Chantziara, Chrysanthi Sklavou, Yannick Hourmant, Nicolas Grillot, Job van Steenkiste, Mathieu van der Jagt, Romain Pirracchio, Abdelraouf Akkari, Mohamed Abdelaty, Ahmed Hashim, Yoann Launey, Elodie Masseret, Sigismond Lasocki, Soizic Gergaud, Nicolas Mouclier, Sulekha Saxena, Avinash Agrawal, Shakti Bedanta Mishra, Samir Samal
Journal: Intensive Care Medicine (2022)
Intracranial pressure pulse morphology: the missing link?
Authors: Sérgio Brasil
Journal: Intensive Care Medicine (2022)

Hawryluk et al. made a comprehensive report on the intracranial pressure (ICP) knowledge historical evolution, and its physiological aspects and rationale for establishing the ranges of safety and thresholds for therapeutic interventions when intracranial hypertension overcomes (IHT) [1].However, these authors stated that the ideal ICP value to trigger dedicated therapy is still not known with certainty.Accordingly, Wijdicks in another recent seminal publication stated: "the use of numeric thresholds does not tell the full picture of changes in autoregulation and cellular dysfunction.We have to come to realize that refractoriness of increased ICP is more important than ICP values" [2].The key for patient individualization regarding ICP monitoring may be harbored by ICP pulse morphology.Recently, Nucci et al. observed the ICP waveform (ICPW) changes according to variations in intracranial volume [3] (Fig. 1).When the tidal peak (P2) acquires an amplitude higher than the upstroke peak (P1) it is known that the intracranial space has lost its compensatory reserve, with impairment in intracranial compliance (ICC) [3].Contrary to what was stated by Hawryluk et al. citing a study from 1988, that the ICP pulse morphology is imprecise to reflect ICC, two recent studies have been published on the correlation of ICPW variations against ICP mean values.Brasil et al., assessing the slopes from 41 acute brain injured patients, mainly traumatic, found that, for patients with undamaged skull who underwent exclusively a procedure for installing an ICP monitor, P2 amplitudes 20% higher than P1 amplitudes were correlated with ICP > 20 mmHg [r = 0.72, area under curve (AUC) 0.9, p < 0.001] [4].The authors observed a
Integrative genomic and transcriptomic analyses illuminate the ontology of HER2-low breast carcinomas
Authors: Enrico Berrino, Laura Annaratone, Sara Erika Bellomo, Giulio Ferrero, Amedeo Gagliardi, Alberto Bragoni, Dora Grassini, Simonetta Guarrera, Caterina Parlato, Laura Casorzo, Mara Panero, Ivana Sarotto, Silvia Giordano, Matteo Cereda, Filippo Montemurro, Riccardo Ponzone, Nicola Crosetto, Alessio Naccarati, Anna Sapino, Caterina Marchiò
Journal: Genome Medicine (2022)

Abstract Background The “HER2-low” nomenclature identifies breast carcinomas (BCs) displaying a HER2 score of 1+/2+ in immunohistochemistry and lacking ERBB2 amplification. Whether HER2-low BCs (HLBCs) constitute a distinct entity is debated. Methods We performed DNA and RNA high-throughput analysis on 99 HLBC samples ( n = 34 cases with HER2 score 1+/HLBC-1, n = 15 cases with HER2 score 2+ and ERBB2 not amplified/HLBC-2N, and n = 50 cases with score 2+ and ERBB2 copy number in the equivocal range/HLBC-2E). We compared the mutation rates with data from 1317 samples in the Memorial Sloan-Kettering Cancer Center (MSKCC) BC cohort and gene expression data with those from an internal cohort of HER2-negative and HER2-positive BCs. Results The most represented mutations affected PIK3CA (31/99, 31%), GATA3 (18/99, 18%), TP53 (17/99, 17%), and ERBB2 (8/99, 8%, private to HLBC-2E). Tumor mutational burden was significantly higher in HLBC-1 compared to HLBC-2E/N ( P = 0.04). Comparison of mutation spectra revealed that HLBCs were different from both HER2-negative and HER2-positive BCs, with HLBC-1 resembling more HER2-negative tumors and HLBC-2 mutationally related to HER2-addicted tumors. Potentially actionable alterations (annotated by using OncoKB/ESCAT classes) affected 52 patients. Intra-group gene expression revealed overlapping features between HLBC-1 and control HER2-negative BCs, whereas the HLBC-2E tumors showed the highest diversity overall. The RNA-based class discovery analysis unveiled four subsets of tumors with (i) lymphocyte activation, (ii) unique enrichment in HER2-related features, (iii) stromal remodeling alterations, and (iv) actionability of PIK3CA mutations (LAURA classification). Conclusions HLBCs harbor distinct genomic features when compared with HER2-positive and HER2-negative BCs; however, differences across IHC classes were also unveiled thus dissecting the full picture of heterogeneity across HER2-low disease. The HLBC-2E category harbors most distinctive features, whereas HLBC-1 seems superimposable to HER2-negative disease. Further studies are needed to ascertain whether the four genomic-driver classes of the LAURA classification hold prognostic and/or predictive implications.
CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research
Authors: Dipak Kotecha, Folkert W Asselbergs, Stephan Achenbach, Stefan D Anker, Dan Atar, Colin Baigent, Amitava Banerjee, Birgit Beger, Gunnar Brobert, Barbara Casadei, Cinzia Ceccarelli, Martin R Cowie, Filippo Crea, Maureen Cronin, Spiros Denaxas, Andrea Derix, Donna Fitzsimons, Martin Fredriksson, Chris P Gale, Georgios V Gkoutos, Wim Goettsch, Harry Hemingway, Martin Ingvar, Adrian Jonas, Robert Kazmierski, Susanne Løgstrup, R Thomas Lumbers, Thomas F Lüscher, Paul McGreavy, Ileana L Piña, Lothar Roessig, Carl Steinbeisser, Mats Sundgren, Benoît Tyl, Ghislaine van Thiel, Kees van Bochove, Panos E Vardas, Tiago Villanueva, Marilena Vrana, Wim Weber, Franz Weidinger, Stephan Windecker, Angela Wood, Diederick E Grobbee
Journal: BMJ (2022)

Big data is central to new developments in global clinical science aiming to improve the lives of patients. Technological advances have led to the routine use of structured electronic healthcare records with the potential to address key gaps in clinical evidence. The covid-19 pandemic has demonstrated the potential of big data and related analytics, but also important pitfalls. Verification, validation, and data privacy, as well as the social mandate to undertake research are key challenges. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including patient representatives, clinicians, scientists, regulators, journal editors and industry. We propose the CODE-EHR Minimum Standards Framework as a means to improve the design of studies, enhance transparency and develop a roadmap towards more robust and effective utilisation of healthcare data for research purposes.
Airway-resident T cells from unexposed individuals cross-recognize SARS-CoV-2
Authors: Mariana O. Diniz, Elena Mitsi, Leo Swadling, Jamie Rylance, Marina Johnson, David Goldblatt, Daniela Ferreira, Mala K. Maini
Journal: Nature Immunology (2022)

T cells can contribute to clearance of respiratory viruses that cause acute-resolving infections such as SARS-CoV-2, helping to provide long-lived protection against disease. Recent studies have suggested an additional role for T cells in resisting overt infection: pre-existing cross-reactive responses were preferentially enriched in healthcare workers who had abortive infections1, and in household contacts protected from infection2. We hypothesize that such early viral control would require pre-existing cross-reactive memory T cells already resident at the site of infection; such airway-resident responses have been shown to be critical for mediating protection after intranasal vaccination in a murine model of SARS-CoV3. Bronchoalveolar lavage samples from the lower respiratory tract of healthy donors obtained before the COVID-19 pandemic revealed airway-resident, SARS-CoV-2-cross-reactive T cells, which correlated with the strength of human seasonal coronavirus immunity. We therefore demonstrate the potential to harness functional airway-resident SARS-CoV-2-reactive T cells in next-generation mucosal vaccines.
Long-lasting geroprotection from brief rapamycin treatment in early adulthood by persistently increased intestinal autophagy
Authors: Paula Juricic, Yu-Xuan Lu, Thomas Leech, Lisa F. Drews, Jonathan Paulitz, Jiongming Lu, Tobias Nespital, Sina Azami, Jennifer C. Regan, Emilie Funk, Jenny Fröhlich, Sebastian Grönke, Linda Partridge
Journal: Nature Aging (2022)

The licensed drug rapamycin has potential to be repurposed for geroprotection. A key challenge is to avoid adverse side effects from continuous dosing. Here we show that geroprotective effects of chronic rapamycin treatment can be obtained with a brief pulse of the drug in early adulthood in female Drosophila and mice. In Drosophila, a brief, early rapamycin treatment of adults extended lifespan and attenuated age-related decline in the intestine to the same degree as lifelong dosing. Lasting memory of earlier treatment was mediated by elevated autophagy in intestinal enterocytes, accompanied by increased levels of intestinal LManV and lysozyme. Brief elevation of autophagy in early adulthood itself induced a long-term increase in autophagy. In mice, a 3-month, early treatment also induced a memory effect, with maintenance similar to chronic treatment, of lysozyme distribution, Man2B1 level in intestinal crypts, Paneth cell architecture and gut barrier function, even 6 months after rapamycin was withdrawn.
Tumor immune contexture is a determinant of anti-CD19 CAR T cell efficacy in large B cell lymphoma
Authors: Nathalie Scholler, Regis Perbost, Frederick L. Locke, Michael D. Jain, Sarah Turcan, Corinne Danan, Edmund C. Chang, Sattva S. Neelapu, David B. Miklos, Caron A. Jacobson, Lazaros J. Lekakis, Yi Lin, Armin Ghobadi, Jenny J. Kim, Justin Chou, Vicki Plaks, Zixing Wang, Allen Xue, Mike Mattie, John M. Rossi, Adrian Bot, Jérôme Galon
Journal: Nature Medicine (2022)

Axicabtagene ciloleucel (axi-cel) is an anti-CD19 chimeric antigen receptor (CAR) T cell therapy approved for relapsed/refractory large B cell lymphoma (LBCL) and has treatment with similar efficacy across conventional LBCL subtypes. Toward patient stratification, we assessed whether tumor immune contexture influenced clinical outcomes after axi-cel. We evaluated the tumor microenvironment (TME) of 135 pre-treatment and post-treatment tumor biopsies taken from 51 patients in the ZUMA-1 phase 2 trial. We uncovered dynamic patterns that occurred within 2 weeks after axi-cel. The biological associations among Immunoscore (quantification of tumor-infiltrating T cell density), Immunosign 21 (expression of pre-defined immune gene panel) and cell subsets were validated in three independent LBCL datasets. In the ZUMA-1 trial samples, clinical response and overall survival were associated with pre-treatment immune contexture as characterized by Immunoscore and Immunosign 21. Circulating CAR T cell levels were associated with post-treatment TME T cell exhaustion. TME enriched for chemokines (CCL5 and CCL22), γ-chain receptor cytokines (IL-15, IL-7 and IL-21) and interferon-regulated molecules were associated with T cell infiltration and markers of activity. Finally, high density of regulatory T cells in pre-treatment TME associated with reduced axi-cel-related neurologic toxicity. These findings advance the understanding of LBCL TME characteristics associated with clinical responses to anti-CD19 CAR T cell therapy and could foster biomarker development and treatment optimization for patients with LBCL.
Socioeconomic roots of academic faculty
Authors: Allison C. Morgan, Nicholas LaBerge, Daniel B. Larremore, Mirta Galesic, Jennie E. Brand, Aaron Clauset
Journal: Nature Human Behaviour (2022)

Despite the special role of tenure-track faculty in society, training future researchers and producing scholarship that drives scientific and technological innovation, the sociodemographic characteristics of the professoriate have never been representative of the general population. Here we systematically investigate the indicators of faculty childhood socioeconomic status and consider how they may limit efforts to diversify the professoriate. Combining national-level data on education, income and university rankings with a 2017-2020 survey of 7,204 US-based tenure-track faculty across eight disciplines in STEM, social science and the humanities, we show that faculty are up to 25 times more likely to have a parent with a Ph.D. Moreover, this rate nearly doubles at prestigious universities and is stable across the past 50 years. Our results suggest that the professoriate is, and has remained, accessible disproportionately to the socioeconomically privileged, which is likely to deeply shape their scholarship and their reproduction.
Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer
Authors: Rami S. Vanguri, Jia Luo, Andrew T. Aukerman, Jacklynn V. Egger, Christopher J. Fong, Natally Horvat, Andrew Pagano, Jose de Arimateia Batista Araujo-Filho, Luke Geneslaw, Hira Rizvi, Ramon Sosa, Kevin M. Boehm, Soo-Ryum Yang, Francis M. Bodd, Katia Ventura, Travis J. Hollmann, Michelle S. Ginsberg, Jianjiong Gao, Rami Vanguri, Matthew D. Hellmann, Jennifer L. Sauter, Sohrab P. Shah
Journal: Nature Cancer (2022)

Immunotherapy is used to treat almost all patients with advanced non-small cell lung cancer (NSCLC); however, identifying robust predictive biomarkers remains challenging. Here we show the predictive capacity of integrating medical imaging, histopathologic and genomic features to predict immunotherapy response using a cohort of 247 patients with advanced NSCLC with multimodal baseline data obtained during diagnostic clinical workup, including computed tomography scan images, digitized programmed death ligand-1 immunohistochemistry slides and known outcomes to immunotherapy. Using domain expert annotations, we developed a computational workflow to extract patient-level features and used a machine-learning approach to integrate multimodal features into a risk prediction model. Our multimodal model (area under the curve (AUC) = 0.80, 95% confidence interval (CI) 0.74-0.86) outperformed unimodal measures, including tumor mutational burden (AUC = 0.61, 95% CI 0.52-0.70) and programmed death ligand-1 immunohistochemistry score (AUC = 0.73, 95% CI 0.65-0.81). Our study therefore provides a quantitative rationale for using multimodal features to improve prediction of immunotherapy response in patients with NSCLC using expert-guided machine learning.
Contemporary Applications of Machine Learning for Device Therapy in Heart Failure
Authors: Nitesh Gautam, Sai Nikhila Ghanta, Alex Clausen, Prachi Saluja, Kalai Sivakumar, Gaurav Dhar, Qi Chang, Deeptankar DeMazumder, Mark G. Rabbat, Stephen J. Greene, Marat Fudim, Subhi J. Al’Aref
Journal: JACC Heart Failure (2022)
Long-Term Outcomes After Atrial Switch Operation for Transposition of the Great Arteries
Authors: Craig S. Broberg, Alexandra C. van Dissel, Jessica Minnier, Jamil Aboulhosn, Robert M. Kauling, Salil Ginde, Eric V. Krieger, Fred Rodriguez, Tripti Gupta, Sangeeta Shah, Anitha S. John, Timothy Cotts, W. Aaron Kay, Marissa Kuo, Cindy Dwight, Patricia Woods, Jeremy Nicolarsen, Berardo Sarubbi, Flavia Fusco, Petra Antonova, Susan Fernandes, Jasmine Grewal, Jonathan Cramer, Paul Khairy, Pastora Gallego, Clare O’Donnell, Jane Hannah, Mikael Dellborg, Carla P. Rodriguez-Monserrate, Isabelle Vonder Muhll, Stephen Pylypchuk, Anthony Magalski, Frank Han, Adam M. Lubert, Joseph Kay, Elizabeth Yeung, Jolien Roos-Hesselink, David Baker, David S. Celermajer, Luke J. Burchill, William M. Wilson, Joshua Wong, Shelby Kutty, Alexander R. Opotowsky
Journal: Journal of the American College of Cardiology (2022)
Validated Model for Prediction of Adverse Cardiac Outcome in Patients With Fabry Disease
Authors: Christopher Orsborne, Joshua Bradley, Laura J. Bonnett, Luke A. Pleva, Josephine H. Naish, David G. Clark, Nik Abidin, Peter Woolfson, Gaetano Nucifora, Matthias Schmitt, Ana Jovanovic, Christopher A. Miller, Anna B. Reid
Journal: Journal of the American College of Cardiology (2022)

The cardiac manifestations of Fabry disease are the leading cause of death, but risk stratification remains inadequate. Identifying patients who are at risk of adverse cardiac outcome may facilitate more evidence-based treatment guidance. Contemporary cardiovascular cardiac magnetic resonance biomarkers have become widely adopted, but their prognostic value remains unclear. The objective of this study was to develop, internally validate, and evaluate the performance of, a prognostic model, including contemporary deep phenotyping, which can be used to generate individual risk estimates for adverse cardiac outcome in patients with Fabry disease. This longitudinal prospective cohort study consisted of 200 consecutive patients with Fabry disease undergoing clinical cardiac magnetic resonance. Median follow-up was 4.5 years (IQR: 2.7-6.3 years). Prognostic models were developed using Cox proportional hazards modeling. Outcome was a composite of adverse cardiac events. Model performance was evaluated. A risk calculator, which provides 5-year estimated risk of adverse cardiac outcome for individual patients, including men and women, was generated. The highest performing, internally validated, parsimonious multivariable model included age, native myocardial T1 dispersion (SD of per voxel myocardial T1 relaxation times), and indexed left ventricular mass. Median optimism-adjusted c-statistic across 5 imputed model development data sets was 0.77 (95% CI: 0.70-0.84). Model calibration was excellent across the full risk profile. This study developed and internally validated a risk prediction model that accurately predicts 5-year risk of adverse cardiac outcome for individual patients with Fabry disease, including men and women, which could easily be integrated into clinical care. External validation is warranted.